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Did we hit some sort of technical inflection point in the last couple of weeks or is this just coincidence that all of these ML papers around high quality proce
by jianshen 4y ago
Did we hit some sort of technical inflection point in the last couple of weeks or is this just coincidence that all of these ML papers around high quality procedural generation are just dropping every other day?
- macrolocal 4y agoConference season?
- sirianth 4y agoyay
- deleted 4y ago[deleted]
- layer8 4y agoFrom the abstract: “We introduce a loss based on probability density distillation that enables the use of a 2D diffusion model as a prior for optimization of a parametric image generator. Using this loss in a DeepDream-like procedure, we optimize a randomly-initialized 3D model (a Neural Radiance Field, or NeRF) via gradient descent such that its 2D renderings from random angles achieve a low loss.” This seems like basically plugging a couple of techniques together that already existed, allowing to turn 2D text-to-image into 3D text-to-image.
- blurbleblurble 4y agoTime and time again these ML techniques are proving to be wildly modular and pluggable. Maybe sooner or later someone will build a framework for end to end text-to-effective-ML-architecture that will just plug different things together and optimize them.
- lbotos 4y agoI think this is what huggingface (github for machine learning) is trying with diffusers lib: https://huggingface.co/docs/diffusers/index https://huggingface.co/docs/diffusers/index They have others as well.
- blurbleblurble 4y agoCool stuff. But who is working on the text-to-ML-architecture thing?
- blurbleblurble 4y agoFascinating stuff! But who is working on the text-to-ML-architecture thing?
- sdan 4y ago> This seems like basically plugging a couple of techniques together that already existed as with a majority of ML research
- anigbrowl 4y agoTrue (I made such a proposal myself a few hours ago, albeit in vaguer terms). The thing is deployment infrastructure is good enough now that we can just treat it as modular signal flows and experiment a lot without having to engineer a whole pile of custom infrastructure for each impulsive experiment.
- ramesh31 4y ago>as with a majority of ML research Plus "we did the same thing, but with 10x the compute resources". But yeah.
- WithinReason 4y agoIsn't that what the Singularity was described as a few decades ago? Progress so fast it's unpredictable even in the short term.
- rileyphone 4y agoSame as it ever was, scientific revolutions arrive all at once, punctuating otherwise uneventful periods. As I understand, the present one is the product of the paper "Attention is all you need": https://arxiv.org/pdf/1706.03762.pdf https://arxiv.org/pdf/1706.03762.pdf.
- visarga 4y ago... that one has 52K citations, and the 2D to 3D paper "NeRF: Representing Scenes as Neural Radiance Fields for View Synthesis" with 1488 citations. https://arxiv.org/abs/2003.08934 https://arxiv.org/abs/2003.08934
- deleted 4y ago[deleted]
- beambot 4y ago> This seems like basically plugging a couple of techniques together that already existed [...] In his Lex Fridman interview, John Carmack makes similar assertions about this prospect for AGI: That it will likely be the clever combination of existing primitives (plus maybe a couple novel new ones) that make the first AGI feasible in just a couple thousand lines of code.
- aliqot 4y agoThat's a great example that reminds me of another one: there was nothing new about Bitcoin conceptually, it was all concepts we already had just in a new combination. IRC, Hashing, Proof of Work, Distributed Consensus, Difficulty algorithms, you name it. Aside from Base58 there wasn't much original other than the combination of those elements.
- stavros 4y agoBase58 really should have been base57.
- aliqot 4y agoHello Stavros, I agree. When I look at the goals that base58 sought to achieve, (eliminating visually similar characters) I couldn't help but wonder why more characters were not eliminated. There is quite a bit of typeface androgyny when you consider case and face.
- stavros 4y agoYeah, I don't know why 1 was left in there, seems like a lost opportunity. Discarding l, I, 0, O, but then leaving 1? I wonder why.
- aliqot 4y agoI can only assume it was for a superstitious reason so that the original address prefixes could be a 1. This is the only sense I can make from it.
- anigbrowl 4y agoThey're AI generated, the singularity already happened but the machines are trying to ease us into it.
- samstave 4y agoScary fn thought! and I agree with you! And the OP comment its by the magnanimous/infamous AnigBrowl You need to start doing AI legal admin ( I dont have the terms, but you may - we need legal language to control how we deal with AI) and @dang - kill the gosh darn "posting too fast" thing Jiminey Crickets I have talked to you abt this so many times...
- bhedgeoser 4y ago> Scary fn thought! I'm a kotlin programmer so it's a scary fun thought for me.
- LordDragonfang 4y ago"You're posting too fast" is a limit that's manually applied to accounts that have a history of "posting too many low-quality comments too quickly and/or getting into flame wars". You can email dang (hn@ycombinator.com) if you think it was applied in error, but if it's been applied to you more than once... you probably have a continuing problem with proliferating flame wars or posting otherwise combative comments.
- ecmascript 4y agoI think you also can get it by just having unpopular opinions. Hackernews used to be much more nuanced than it is today imo.
- samstave 4y agoUhm... did you even check my account age ((and my old one is two years older))
- eurasiantiger 4y ago
- deleted 4y ago[deleted]
- alphabetting 4y agoMaybe deadline for neurips which is coming up?
- grandmczeb 4y agoThis was submitted to ICLR
- vintermann 4y agoWhose full paper submission deadline was also 2 days ago. This should be further up than all the speculation about AI accelerationism. There's a very simple explanation why a lot of awesome papers come out right now, it's prestigious conference paper deadlines.
- darkhorse222 4y agoI think DALLE really kicked things into high gear.
- samstave 4y agoTHIS WTF - the singularity is closer than we thought!!!
- dr_dshiv 4y agoIt’s called the technological singularity. Pretty fun so far!
- AStrangeMorrow 4y agoThis isn't what is usually meant by "technological singularity". It is an inflection point where technology growth becomes incontrollable and unpredictable, usually theorized to be cause by a self improving agent (/AI) that becomes smarter with each of its iterations. This is still standard technological progress, human control, even if very fast
- visarga 4y agoIt's not really "human controlled". It's an evolutionary process, researchers are scanning the space of possibilities, each with a limited view, but in aggregate it has an emergent positive trend.
- dr_dshiv 4y agoIt’s basically when AI starts self-improving. I think this started with large language models. They are central to these developments. Complete autonomy is not required for AGI-nor therefore for the singularity. Whatever it is, this is a massive phase shift.
- Workaccount2 4y agoSD is open source (for real open source) and the community has been having a field day with it.
- ImprobableTruth 4y agoMy hot take is that we're merely catching up on until recently unutilized hardware improvements. There's nothing 'self-improving', it's largely "just" scaled up methods or new, clever applications of scaled up methods. The pace at which methods scale up is currently a lot faster than hardware improvements, so unless these scaled up methods become incredibly lucrative (not impossible), I think it's quite likely we'll soon-ish (a couple years from now) see a slowdown.
- gitfan86 4y agoIt has become clear since alphaGo that intelligence is an emergent property of neural networks. Since then the time and cost requirements to create a useful intelligence have been coming down. The big change was in August when Stable Diffusion was able to run on consumer hardware. Things were already accelerating before August, but that has really kicked up the speed because millions of people can play around with it and discover intelligence applications, especially in the latent space.
- the8472 4y agoThis has been going on for years. The applications are just crossing thresholds now that are more salient for people, e.g. doing art.
- nbardy 4y agoWe've hit a couple of inflection point. The numbers of researchers and research labs scaled up that there is now many well funded teams with experience. Public tooling and collaboration has reached a point where research happen across the open internet between researchers at a pace that wasn't before possible. Common Crawl, stable diffusion, hugging-face, etc...) All the techniques that took years in small labs to prove as viable are now getting scaled up across data and people in front of our eyes.
- learndeeply 4y agoPartially coincidence, but also ICLR submission deadline was yesterday, so now papers can be public.